SNF PhD position in Medical NLP

We are looking for a PhD student for our SNF project ”Medical, Multilingual, and Privacy-Preserving Natural Language Processing (M2P2-NLP)” passionate about working on medical problems and can help us create AI tools in the medical field, particularly in oncology and radiology.

🧑🏼‍🔬 You will be someone who loves to do research, design, and build novel AI models. You are used to working in a research environment. You will have experience in building and evaluating machine learning models and preferably have knowledge and experience in the text and image processing domain.

👩‍💼 You will join as an SNF PhD student to the Medical Language Technology group in the Krauthammer Lab at the University of Zurich and will have the opportunity to collaborate with multiple research teams at the Hospital University of Zurich and the University of Zurich.

What will you be doing?

In this position, you’ll be working at the heart of our NLP Team, helping us work on the medical AI assistant tools for oncology and/or radiology. You will also help us create a high-quality AI system and take ownership of implementation. This would include the following:

• Explore the state-of-the-art multi-modal multi-lingual Agentic AI models
• Design and implement Multi-modal Multi-lingual NLP algorithms and models.
• Adapting “off-the-shelf” solutions for our research projects.
• Contribute to a high-quality codebase, and develop tests where necessary.
• Collaborate with other research fellows, especially with our SNF Project Team
• Develop and train large multimodal AI models for processing and discovery of medical data especially on oncology data and for Information Extraction from Clinical Notes, and Text de-identification
• Present, write, and publish papers at conferences

Who are you?

Education

• Minimum: M.Sc. in a related field or equivalent experience

Experience

• At least +1 years of experience in computational sciences, including Machine Learning, computer sciences, computer vision, Computational Linguistics, and other relevant fields.
• Expertise in large AI models, computational methods, data analysis, software and algorithm development, and modeling.
• Ability to do original and outstanding research in computational sciences and its relevant field.
• Ability to work well independently as well as in a collaborative team environment, in-person as well as via online channels.
• Ability to handle multiple projects at the same time
• Ability to present research and other types of work, internally and externally
• Having coding skills in Python and passionate about the software development side of things!
• Capable of building user-facing APIs that expose a range of NLP features as a service
• Having experience in using most modern frameworks for deep learning (PyTotch, Hugging Face) as well as for software development (Git, Linux) and GPU cluster (i.e., Slurm, Singularity).
• The applicant must have native proficiency in the German language.

Preferred Experience in:

• Medical NLP downstream tasks
• Multi-modal Multi-lingual ML models and Agentic AI system
• Knowledge about retrieval augmented generation (RAG)
• Working at a hospital or within a healthcare
• Working with privacy-sensitive data

What we offer:

We offer you freedom for ideas and the opportunity to use your experience and expertise effectively to contribute to and promote the medical AI assistant tools.

• active participation in the highly complex IT landscape
• a responsible and varied job
• a motivated and committed team that values mutual support, appreciation, and respect
• an innovative, interdisciplinary, and highly specialized work environment
• access to state-of-the-art infrastructure
• outstanding working conditions at the University of Zurich
• The position is an SNF PhD, full-time position 80% for 4 years
• Access to Swiss AI GPU clusters

Application

• Starting date: as soon as possible or upon agreement
• Deadline: Thursday 21st November, 2024
• Duration: 4 years
• Please submit your CV with a publication list to claudia.stenger-gysling@uzh.ch
• If you are selected for the second interview: Two (2) letters of recommendation, submitted confidentially by the letter writers to michael.krauthammer@uzh.ch
• If you need more detailed information about the role, please contact farhad.nooralahzadeh@uzh.ch